Liquidity sensing and smart order routing

Regulation in both the US and Europe is having a significant impact on smart order routing in relation to best execution and venue selection. An important part of the routing process revolves around the sensing of hidden liquidity.

AT talks to five major sellside providers about their take on the
technology and the challenges for liquidity sensing and smart
order routing

With:

Richard Balarkas, Managing Director and Head of AES Sales at
Credit Suisse

If smart order routing is to be truly smart, is there an
implicit requirement Post RegNMS/MiFID for the sellside provider
to be connected to every possible execution venue?

Balarkas: While regulation such as MiFID
certainly raises the bar in this respect, it doesn't make this a
specific requirement. However, there is still the need to remain
competitive, so one therefore cannot afford to ignore any venue
that has reasonable liquidity.

Bayliss: I think the pressure to connect will
come more from competitive considerations than regulation.
Ultimately, the decision whether or not to connect to individual
pools of liquidity will be determined by their current or
forecast volumes. The proliferation of venues is also likely to
lead to partnerships being created between venues sharing
liquidity information.

Hunt: The answer in Europe is not necessarily.
MiFID states that asset managers as well as broker dealers
(investment firms generally) must have a "best execution" policy.
If in that policy they state that they will access each and every
available venue, then that is what they are obliged to do. MiFID
asks investment firms to consider criteria that they would use in
order to make a routing decision. Within those criteria, price is
obviously the dominant factor, but speed and certainty of
execution also have to be considered. Regarding certainty of
execution, smart routers will need to have a history of the
likelihood of being hit and the order of magnitude of the
liquidity available at the venue.

Finally, cost is another significant consideration in Europe,
given the relatively inefficient clearing infrastructure and
potentially high fixed costs associated with dealing on
alternative venues.

Self: I think one has to connect to liquidity
venues if they are seen as being beneficial to providing best
execution. There may be some venues that appear to exhibit
sufficient liquidity, but because of the nature and activity of
the other participants on those venues connecting might not
actually improve the execution quality for our clients. Therefore
there is a need to monitor the various execution venues on an
ongoing basis and only connect to those that offer the "right"
sort of liquidity.

Yuster: For RegNMS, brokers have to be directly
connected to all eleven Self-Regulatory Organizations (SROs) or
allow those SROs to re-route orders on their behalf (which is
less than ideal in terms of best execution, for reasons of
latency and potential order concentration at a single venue).
However, this is still incomplete connectivity, because it omits
ECNs and dark pools.

In order to achieve best execution, a broker needs to be
connected to all these venues and be processing all the market
data from all their books. In this last respect, in order to
optimise performance, we believe it is important to process the
full book of data (not just top of book) directly from source and
not via a third party provider.

In Europe, the regulatory environment is moving towards a
principles-based interpretation of best execution. It's our
understanding that the buyside will have to prove that they have
the infrastructure and processes to achieve best execution. Over
the long term, it will become a standard requirement that smart
routers access all available public venues, private venues will
continue to be subject to individual client/ broker agreements.

Required to connect everywhere?

Are "compliance snapshots" (the capture of contemporaneous
trading and quote information to substantiate order routing
decisions) likely to prove a significant hurdle for the
sellside?

Balarkas: Such snapshots aren't a particular
obstacle to larger sellside participants, who will be collecting
that data anyway, but nor are they of much assistance in
guaranteeing you got the best result. The problem with the
concept of a compliance snapshot is that it is only applicable to
a market/situation where one is supposed to be chasing the best
price, regardless of all other circumstances.

In practice this is not ideal because one often finds that what
appears to be the best price isn't actually available if one
tries to trade against it. A relatively common problem in this
respect is the ghost price that appears briefly but disappears by
the time an order arrives. Over time one becomes aware of the
venues and situations where this is likely to happen. Therefore
truly advanced best execution actually involves deploying that
expertise so as not to route orders there and miss real
opportunities, even if the price displayed currently appears to
be the best.

Bayliss: We don't think this will represent a
problem. Apart from the fact that larger sellside firms will be
collecting this data anyway, existing market data vendors have
already started to make it clear that they will be stepping into
this space. We expect product offerings from these vendors to
include the ability to replicate the theoretical combined order
book and incorporate all information available to the trader at
the time of execution (for example whether or not a quote is
protected).

Hunt: For some smaller sell side firms this
could potentially prove a rather expensive endeavour. Therefore I
suspect that some of them will try to resolve this by using
vendor-based solutions.

In our case we don't see this as a problem, as we have
reconfigured our systems so that they are scanning additional
data feeds for alternative liquidity resources. We also use
time-stamping to ensure that the order management systems are
synchronised and that we have a comprehensive audit trail. In
addition, the post trade reports we send to all customers can
include this granular level of detail if they require it.

Jackson: Smart routing technology, full book
market data as well as trade and quote databases are all
expensive to build, maintain and require significant expertise.
Therefore probably only the top ten or fifteen brokers will be
able to do this and amortise the cost over global businesses
across their order flow, which will likely make compliance
snapshots a challenge for smaller sellside participants.

It seems likely that a consolidated tape of real time publicly
displayed quotes will be a standard requirement in the market.
However, the question whether historical and trade reporting
information will be available in a consolidated form is less
certain, the Merrill Lynch supported project Boat is a key
initiative to address this.

Self: This could potentially be a problem for
smaller sellside participants that are only connected to one or
two venues and don't have the capability of aggregating all the
market data in one place. The challenge then is how to obtain a
sufficiently comprehensive view of the market. If third-party
data vendors can provide this, then all well and good, but if
they cannot then the challenge is significant.

From our perspective we don't see this as a problem, as we are
collecting all this data anyway. However, there is a need to make
an evaluation whenever a new trading venue emerges. As a result,
we might well be collecting compliance snapshot data for a
particular venue before we were actually trading live on it. I
think it is prudent to be collecting data from a market even
before you have an actual trading link to it, as this obviously
helps in assessing the quality of the venue for possible order
execution.

Compliance snapshots - an overwhelming task?

Are the search costs associated with smart order routing now
so small as to have negligible effect on price priority
calculations?

Balarkas: The cost of searching is now pretty
minimal. The only substantive cost associated with searching (as
opposed to simply trading on the first available venue) is the
opportunity cost. There is also obviously a certain amount of
latency involved in looking at more than one venue, but if your
systems are fast enough that is very small.

There has been a fair amount of academic research in this area,
which has been largely inconclusive. However, from a practical
perspective we don't regard search costs as being problematic.

Bayliss: Search costs are not insignificant and
so any disparity between venues will continue to be an input into
price priority calculations. However, while the initial set up
costs for connecting to a trading venue are considerable, if the
order flow to that venue is substantial then the connection costs
will be quickly amortised over time.

Self: It is expensive to connect to multiple
venues, but the need is there. Particularly in the US where there
are a lot of crossing networks it is very expensive, but because
of regulatory pressure it is just one of the costs of trading. If
there are trading venues that offer sufficient liquidity and they
improve best execution quality, then you have to connect.

You obviously have to factor in the individual costs of
connecting to a venue (which may vary widely) when calculating
search costs. This could be a self-fulfilling prophecy in that
the costs of connecting to and trading on a venue could have an
impact over the longer term on the liquidity available there.

Yuster: The "search cost" associated with smart
order routing may be viewed as the latency involved in re-routing
part of an order from one destination to another as well as the
loss of priority in the queue on an individual order book when
doing so. In many cases, as liquidity fragments across more
venues, these factors are outweighed by the opportunity of
achieving a better price and/or to exhaust hidden reserves on
another venue.

However, certain stocks that trade at fewer price points during
the day will have longer queue times, and for these stocks
retaining an order's position in the order book is essential. In
these cases, the cost of removing an order from one venue and
moving to another may be much greater.

If a trading venue is consistently failing to show liquidity,
should it still be scanned as part of the smart order routing
process?

Balarkas: If one is already connected to a
venue, then there is nothing to lose by scanning it. If it is
very inactive, it might not be the venue one pings first or
places one's own passive orders. However, once connected, there
is little or nothing to be lost in trying it out. There may be a
point at which one disconnects from such a venue in order to save
unnecessary costs, but the liquidity would have to be pretty dire
to justify that step.

Toby Bayliss: "...the competition among trading venues is
serving to keep the costs of connection down..."

Bayliss: If it is felt that the trading venue
has in certain cases the potential to still be a valuable source
of liquidity, then it will continue to be scanned as part of the
order routing process. If liquidity falls to such an extent that
costs of accessing the venue do not offset the perceived price
benefits, then scanning would cease. Similarly, if accessing a
very illiquid trading venue reveals too much information about
your particular trading strategy, it should be omitted from the
scanning process.

Particularly in the US, the competition among trading venues is
serving to keep the costs of connection down, so in general they
are not disproportionately high in relation to the expected
return from executing trades on those venues.

The position In Europe is currently slightly different. For
example, I don't believe a single stock trader would see much
value in being connected to a Continental exchange to trade a
major UK security. Such a stock may have an alternative listing
on the Continent, but the liquidity is likely to be minimal in
comparison to the LSE.

Hunt: Possibly, but it is important to note that
there is a difference between smart routing and algorithmic
trading - their objectives are different. Algos are the liquidity
seekers and proactively scan all venues including internal. Algos
can be effective at that because they have knowledge of the
parent order, trading objective and benchmark.

So, you could say smart routers optimise the routing of child
orders to ensure the best child price is obtained across venues,
and algos aim to achieve the best execution result for the whole
order size, over the life of the order, by seeking out hidden
liquidity. Both look at previous history to develop a sense as to
where you are likely to be filled, but the reality is that smart
routers are not in fact scanning, as algorithms do, but rather
receiving information. This information comes from two distinct
sources: public venues that provide quote feeds which we
consolidate and non-displayed venues, such as liquidity that is
internal to a broker dealer.

Self: I think a twofold approach is appropriate
here. One is historical - obviously you do historical analysis as
to where liquidity is available in terms of regional exchanges
and other liquidity venues. However, while trading your systems
also need to keep track of where you are finding liquidity on a
particular day. So if you aren't finding liquidity on a certain
venue on a particular day then you might start trying other
venues first.

Nevertheless, there is an opportunity cost to consider when
deciding venue priority. If you ping a venue in considerable
size, then that obviously ties up a lot of your order, so a
balance of historical and real time liquidity profiles should
ideally be considered when making the priority and weighting
decision.

However, if you have a connection to a liquidity venue anyway,
there isn't any reason not to test it for liquidity, as there
isn't an additional cost for pinging it.

Yuster: The historical liquidity available on a
particular destination is an important factor in a smart routing
decision, and at the start of a trade, the weighting given to
each venue will be based on the historical liquidity available.
Prioritisation of trading venue is then revised dynamically based
on available liquidity.

Additionally, we believe that clients should have the option to
decide for themselves by setting their own individual rules as to
which venues our smart order router polls when searching for
liquidity. Some clients want to limit what they publish on
certain less discreet venues - often only taking liquidity from
rather than posting liquidity to that platform. In addition,
clients have the option to prioritise venue polling on the basis
of the real-time hit rate achieved for a particular name on that
venue.

Pulling the plug on illiquid venues

Brad Hunt: "MiFID asks investment firms to consider
criteria that they would use in order to make a routing
decision."

Do you feel that smart order routing systems are now so
effective in consolidating the various trading venues that they
already replicate/exceed the claimed liquidity benefits of a
centralised limit order book?

Balarkas: A common view amongst economists and
one that I share is that exchanges should be natural monopolies.
By that I mean that there is no reason why a single venue cannot
provide all the functionality and benefits of reduced search
costs, liquidity, and pre/post trade transparency. If such a
venue existed it would exist alone, as there would be no reason
for competing venues to exist. However this assumption depends
upon the natural monopoly not extending into monopoly pricing,
which is a common concern.

I think that the process of aggregating trading venues does
actually replicate many of the single exchange benefits outlined
above. This creation of a virtual single market probably matches
the liquidity benefits of a centralised book, but I am not sure
it exceeds them.

On the other hand, the fragmented model adds value in terms of
maintaining competition and therefore bearing down on costs.
There are other benefits as well - for example, if one venue is
prepared to price at a finer tick size than others, then that
represents a major advantage.

Bayliss: The most efficient, fair and effective
market is based around a centralised limit order book. This
however assumes that the centralised order book has all the
required functionality, order types, speed and also operates at
minimal cost. Unfortunately the monopoly effect has lead to
centralised trading venues failing in one or more of these areas.
The efficiency of consolidated order books ensures that the basic
functionality of a centralised exchange is matched.

In addition, there are potential additional benefits derived from
liquidity hidden from a traditional exchange. For example, the
ability to execute large blocks of stock by accessing dark pools
of liquidity and trading with less impact will be a significant
trading benefit. Other advantages, such as being able to trade
within the spread and the availability of additional order types,
will offset the setup costs of smart order routing systems. The
overall result is that smart order routing across multiple venues
represents an overall net gain versus a centralised limit order
book.

Hunt: Particularly in the US, where liquidity
fragments across a number of different ECNs, I think smart
routers have been very effective in consolidating that liquidity.
They are effectively showing participants a virtual centralised
limit order book. However, the liquidity that makes up that
virtual book is still residing in different systems, so there is
no single location for price and time priority executions to
occur. So, while they are effective at consolidating liquidity
across market centres and venues, they will never replace one
central limit order book.

This of course prompts the question of whether a single central
limit order book in which all the liquidity resides is really the
end objective. At this point, we would say no. One of the things
that multiple trading venues and smart order routing have
achieved is a reduction in overall trading costs by creating more
competition between exchanges and tightening spreads.

Jackson: A single centralised limit order book
effectively represents a monopoly on trading with all the
associated implications of monopoly pricing due to lack of
competition. Therefore, in terms of competitive pricing, you
could argue that the smart order routing across multiple venues
offers lower costs due to competition.

By offering unprecedented access to additional, undisplayed
inventory - both hidden reserves and dark pool liquidity - smart
order routers can also be said to increase available liquidity
beyond the visible exchange order book. In addition, it should be
noted that smart order routers do more than just aggregate
liquidity, they also provide clients with a suite of tactical
strategies to satisfy a variety of trading objectives.

Self: I think that for those who have effective
smart order routing then this is certainly the case. Entities
that are supplying best execution services simply have to have
this kind of technology available. If they use this in the
correct way, then it does indeed largely replicate a centralised
limit order book.

The one thing it doesn't do is take account of the
unsophisticated market participant. For example, if you happen to
be sitting upon the best bid in a particular liquidity venue and
an unsophisticated participant hits a bid lower than yours
somewhere else, then that still affects your execution
deleteriously. However, regulation is effectively compelling
trading sophistication, so over time even this caveat should
disappear.

Chris Jackson: "A single centralised limit order book
effectively represents a monopoly on trading..."

Is smart order routing that omits the sensing of hidden
liquidity intrinsically dumb?

Balarkas: Yes!

Bayliss: The short answer is of course yes. The
idea of routinely neglecting to search hidden pools contradicts
the most basic concepts of transaction cost analysis. Executing
with hidden liquidity can enable significant volume to be
transacted with minimal impact.

However, if you are trading an order that represents a very small
percentage of the daily volume in a liquid name, targeting hidden
liquidity may not be necessary to facilitate best execution.
Under these circumstances, if you are happy to get done just at
the touch, then of course you don't need to search all the venues
for liquidity anyway. There is not a lot of point pinging all the
exchanges and trying to find out what is going on in all dark
pools if all you are trying to do is a thousand Vodafone shares.

Hunt: A smart order router that only accesses
displayed liquidity on public venues is not accessing all the
liquidity available in the market place at that given point in
time. Therefore, if you think access to all available liquidity
is important to achieving your investment or trading objectives,
then you would have to consider that as a factor. We have
discovered that accessing both displayed and non-displayed
liquidity is vital for our smart router. This is because the
non-displayed liquidity component is significant in improving
execution performance and accessing greater size than is
available at the touch price, thereby reducing market impact.

I think it is too early to tell how much difference, in
percentage terms, accessing hidden liquidity actually makes in
terms of performance. It really depends on the size of the order.
However, what we are seeing in Europe is spread compression and
the dispersion of liquidity across the order book. So while touch
spreads are tightening, the weighted spread cost for a larger
order is not necessarily narrowing and that is a result of
existing liquidity being dispersed across a larger number of
tiers. Therefore, while it is too early to say for sure, evidence
suggests that there are significant benefits of non-displayed
liquidity in terms of size improvement at a given price, which
intuitively leads to a lower market impact cost.

Self: The need for sensing hidden liquidity can
differ depending on the situation. For smaller orders where
enough liquidity is available on the touch, sensing hidden orders
may have little material benefit. However, for other situations
where your need for liquidity is greater, it would be a mistake
to omit the sensing of hidden orders. As I said earlier, if you
are already connected to a venue the amount it costs to send an
order to test for hidden liquidity is small. It might cost
fractionally more in certain venues in that you might have to
leave the order there a little bit longer because of the cyclical
nature of other participants' trading.

Yuster: If you are pinging venues for liquidity
and not using the results obtained from that process as an input
to future trading behaviour, then yes that is less than smart.

Smart order routers require extensive databases of statistical
information in order to seek hidden liquidity. A smart router
must have knowledge of the available order types and parameters
at a destination - for example minimum size constraints, support
for iceberg order types - as well as historical statistical
information per venue. For example, an important determinant in
making routing decisions is the typical duration required to rest
in a dark venue in order to maximize fill rates.

Owain Self: "...one of the most effective techniques is
using intelligent learning to optimise your next trade."

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In general terms, which liquidity sensing techniques
do you feel are most likely to be effective?

Balarkas: Historical experience is a significant
input to this. Over time as one continually operates on the same
venues one appreciates where it is easiest to execute trades
against hidden orders. However, while this represents solid
empirical evidence, like any historical data it isn't infallible
for predicting future activity. There is always the possibility
that hidden liquidity will move to another venue for a myriad of
reasons.

On the other hand, if one is trading against more hidden
liquidity on a particular venue, then that in is itself an
incentive for other participants to place more such hidden
liquidity on there. Their desired outcome is for their hidden
orders to be found and traded against and moving to that venue
will obviously facilitate this.

Bayliss: The ability to "ping" multiple sources
or dark liquidity allows dark pools to be probed to detect
interest from other market participants. This is achieved by
simultaneously sending off minimum size orders to each dark pool
to investigate if any appetite exists. This then enables
liquidity to be directed to the venue with the highest
probability of execution.

The "networking" effect is also important; remembering and acting
upon successful destinations from previous orders can improve the
hit rate of which trading venues to target.

The use of a "Dark Book" at the order routing/EMS stage allows
orders to be routed where it is already known that liquidity
exists. It also enables users to specify total order size without
revealing full details to the market or third party dark pool.

Self: Trying multiple sources and using
immediate or cancel orders are very simple ways of accomplishing
this. In general terms, one of the most effective techniques is
using intelligent learning to optimise your next trade.

The key is how you marry this real time learning with historical
experience. Your starting point will always be history, but that
alone is not enough. If you get that marriage right then it will
provide a good insight not only into where liquidity might arise,
but also when and who from.

Sheridan: In general terms the key objective
with most trading strategies is to reduce information leakage. We
have found that algorithms are a very effective tool to seek both
displayed and non-displayed liquidity in a stealthy manner.

A major objective for the investment community is to reduce the
trading costs associated with small and mid-cap securities. There
are a number of different ways of doing that, including:

An effective feedback loop: When trying to access
non-displayed liquidity you need to be smart in the way that
you ping it. This includes trying to achieve a mid-price
execution to see if there are any discretionary order types
in the market. That needs to be supported by a good feedback
loop, so that as you are pinging you utilise the fill rates
on those pings going forward to adjust your trading behaviour
to best effect.

Real and Unreal liquidity events: There are still occasions
when market participants will advertise size in the order
book with the intent of bringing a buyer or seller into the
market. In these circumstances it is important not to look at
the displayed liquidity and assume that it is a liquidity
event. A far more important consideration is whether it is a
real liquidity event and specifically whether or not it is
one that makes showing one's own hand worthwhile.

Assessing the characteristics of certain liquidity requires a
historical understanding of what the order book looks like in
that particular security - for example, hat is the average bid
offer size? Is the event occurring now genuinely significant? Is
it significant in that the current bid/offer spread is tighter
than normal? Just because somebody is offering 100,000 shares
doesn't necessarily mean it is worth trading. If you execute, you
are showing your hand and potentially marking up the balance of
your order.

Yuster: We tend to use a mixture of historical
and real time data to help locate liquidity. Early in a trading
session, we tend to rely more on historical statistics per symbol
and per venue. However, as the session develops, you are able to
see if real time liquidity distribution differs from the
historical profile and accordingly, dynamically adjust your
routing calculations.

Richard Balarkas: "...Money managers have different views
on the risk that is represented by showing their
order..."

Is the cost of developing liquidity sensing algorithms only
justifiable in the case of more volatile stocks with a higher
exposure risk?

Balarkas: No I don't believe that this is the
case. The simple fact is that there are many reasons why people
feel they can achieve alpha but this is not obvious just from the
nature of the stock. Therefore money managers have different
views on the risk that is represented by showing their order and
the effect that will have on the alpha they are trying to
capture. I don't believe that this is mirrored within the
qualities of the stock itself, such as size and volatility.

Bayliss: There are many techniques for sourcing
liquidity that are relevant for both liquid and illiquid names;
as such, the skills and knowledge are directly transferable. The
risks of trading liquid names are less prevalent as there is a
reduced risk of predatory gaming. However executing large size in
liquid names still raises impact issues which trading with dark
pools can reduce.

Jackson: No - you need liquidity sensing
algorithms across the whole universe of stocks for which you
offer smart routing. Volatility is only part of the story,
liquidity is obviously also important - and both these
characteristics of a stock can change hourly. Therefore there are
frequent occasions where finding liquidity outside the current
touch on even low beta utility names has significant client
benefit. Furthermore, the costs of this technology are mostly
fixed so extending the universe of names covered is very
straightforward.

Self: There are a number of factors which
contribute to the overall cost of trading - spread, volatility,
liquidity etc. Any order that is large relative to ADV or in a
stock which has a wide spread will naturally benefit from finding
liquidity and therefore is a good candidate for these algorithms.
Additionally where the trader has high alpha content in their
flow, in any type of stock, the benefit from picking up
non-displayed liquidity and thereby reducing their duration of
execution will be immensely beneficial.

Sheridan: No. We think there are benefits to
finding liquidity in any stock. If you look at the US, whenever
an order is executed in even a large cap name in the order book,
information is released to the market. There are many different
strategies that react to that information that potentially have a
price impact on the stock, even if it is a large cap. So
accessing liquidity in a stealthy manner is vitally important,
irrespective of the market capitalisation or the turnover in the
particular name you are trading.

I think there is definitely a requirement to have a liquidity
seeking component on all security types, not just on those that
are volatile. Ultimately, liquidity sensing becomes a tool that
augments the existing benchmarked algorithmic strategies.
Participants are not just looking to mimic the benchmark; they
are looking for some out-performance, which is where I think
these strategies can be very useful for an active manager.

Peter Sheridan: "This time of day effect is more
exaggerated amoung small and mid-cap securities than
large caps..."

Are liquidity sensing algorithms already starting to make the
use of hidden limit orders redundant?

Balarkas: No not at all. When I place a hidden
limit order I want counterparties to be able to find me but
without moving the price ahead of trading (pre-trade risk). In
practical terms there is simply no way one can accurately model
the depth of an iceberg order. (Though one can make a rough
estimate based upon the amount that is being shown).

Bayliss: Hidden limit orders are necessary when
liquidity is not available at the required level and you wish to
ensure you capture liquidity at that level or better, without
signalling your intentions to the market.

Therefore I would disagree and say that there remains a very
strong case for using hidden limit orders, regardless of the
capabilities of liquidity sensing algorithms. In practical terms
I cannot see any way in which it is anywhere near possible to
recreate the entire order book. Unless you interact with
all the flow how can you actually know what is there?

Self: I don't believe so - in fact liquidity
sensing algorithms are actually making those hidden limit orders
more effective. If the sensing algorithm finds your hidden limit
order then you trade, which is what you want.

The exception is when a counterparty is continually taking your
liquidity in small size to see if you are really there and then
using that information against you in a predatory fashion. This
is why I alluded earlier to the importance before connecting to a
venue of checking whether the activity of other existing
participants is actually prejudicial to your trading.

Sheridan: No, I don't think they are making them
completely redundant. There are tools that can look for hidden
liquidity but there is no guarantee they are finding it all. They
can look at the average bid/offer size, the average trade
size/count and other data to make estimates. However, these are
just informed estimates as to what lies behind the visible order,
so there is still some value to hidden limit

Yuster: No, because there will always be limits
on how accurately you can reconstruct the order book. In the
first instance, you have to send some flow to a venue to gauge
what is there. In the second, historical data is only of value in
predicting what may be in an order book if it is statistically
significant and has a high probability of recurring in the
future. Hidden limit orders will always be an important way of
participating in the market without exposing the order.

Do you believe that the effectiveness of liquidity sensing is
strongly correlated with the time of day? If so, does this imply
that other types of algorithm should be automatically substituted
at certain times of day?

Jarrod Yuster: "...there will always be limits on how
accurately you can reconstruct the order book."

Balarkas: An effective sensing algorithm will
work consistently throughout the day; therefore I cannot see any
reason why one would not wish to use it because the market was
illiquid. Typically more than 75% of all money managers' orders
have negative trend (price moves adversely away from the desired
entry point). On that basis one needs to get trades done faster
than pure participation with visible liquidity will allow, so
there will always be a need to search for and exploit hidden
liquidity.

Bayliss: Every dark pool has its own rules on
how hidden orders are matched, some are continuous, while others
operate on an auction basis at set times of the day. The
discontinuity of the trading in dark pools naturally causes their
effectiveness to be correlated with times of day. Information on
liquidity and auction times are therefore an intrinsic part of
the smart order routing process.

However, despite all these factors, it is interesting to observe
from practical experience that if a robust liquidity sensing
algorithm is being used, no particular time of day seems to yield
better or worse results.

Jackson: There is certainly a strong correlation
between liquidity patterns and time of day. You can clearly see
that the liquidity, volatility, trade frequency and intensity
characteristics of certain markets are very different at points
over the day. It is important that the historical statistics
driving an algorithm are not just daily averages, but specific to
the time of day.

Liquidity seeking algorithms should be able to model liquidity
patterns based on historical statistics but then adjust real-time
to changing market conditions. Our smart routing algorithms did
just that during a recent market outage. When liquidity on the
main market declined, the algorithm compensated by increasing the
proportion of the order worked and executed on alternative
venues.

Self: Depending on the liquidity venue (and
particularly on the larger dark pools with passive institutional
flow) you will definitely see a correlation between the number of
hidden limit orders and the less volatile points of the day.
However, each venue tends to have its own characteristics, which
is why (particularly in the US) we will try certain venues at
certain times during the day, as we know there is likely to be
more liquidity available.

Timing hidden liquidity

Sheridan: I think the answer to the first part
of the question is yes. From a European perspective, there is a
very significant "time of day" effect in European markets. If you
look at the LSE, the bid/offer spread of even large names during
the price discovery period is four or five times wider than the
average spread for the whole day. Liquidity (in terms of
displayed liquidity) is very limited during that period and the
trading cost implication of that is why some clients have
historically tended to avoid trading at this time of day.

This time of day effect is even more exaggerated among small and
mid-cap securities than large caps that have a continuous and
stable order book throughout the day. Volume in small and mid-cap
securities is very often skewed towards the latter part of the
day when more investors are coming into the market.

Generally speaking it is always important to understand the
trading patterns of an individual stock or market, and time of
day is a significant part of that. Therefore algorithms need to
be tuned to take advantage of these characteristics. However, I
don't think it is necessarily a case of using different
algorithms. I suppose the question clients should ask themselves
instead is whether the algorithms they are using take into
account the time of day effect and, if so, how?